Fingerprint identification, which exploits characteristics of fingerprints such as individuality and lifelong invariance, is effective in identifying a user on an information appliance or in information service. In the process of user verification adopting the fingerprint identification, first, a user X inputs his/her fingerprint from a fingerprint input section when making use of an information appliance or information service; next, the inputted fingerprint is collated with previously inputted and stored fingerprint data (referred to as a template) of a registered user A who has the authority to use the information appliance or information service; and the user X is allowed to use the information appliance or information service if both the fingerprints match each other.
For inputting a fingerprint, a two-dimensional sensor input unit having a squarish input screen enough wider than a fingerprint region has been widely employed. However, in order to expand the field of application of the input unit through cost cutting and miniaturization, it is better to provide the input unit with a sensor screen smaller than a fingerprint region and perform the fingerprint verification by using a sequence of partial fingerprint images obtained by moving a finger relative to the small sensor screen (referred to as sweep motion).
There is disclosed a technique as an example of using the small sensor screen in Japanese Patent Application Laid-Open No. HEI10-91769, wherein a two-dimensional image used for verification is composed of a sequence of partial images obtained by sliding a finger on a rectangle, almost one-dimensional line shaped sensor, whose long sides are approximately as wide as a finger and the other sides are much shorter than the long sides, in the direction parallel to the short side. According to the technique, the line shaped sensor sequentially picks up shading images corresponding to ridge patterns of a fingerprint as a finger moves thereon, and thus a sequence of rectangle partial images, in other words, line shaped shading images are inputted one by one to an input unit with the course of time. The partial image obtained by one image pickup is referred to as a frame or a frame image.
FIG. 8 shows the general procedures of the conventional technique as described below to reassemble a series of partial images into a two-dimensional image and perform fingerprint verification when the frame images are sequentially inputted.
{circle around (1)} A physical relationship between an inputted partial image and the adjacent one, namely, two-dimensional distance between the frame images is detected for positioning the images (step S11, S18).
{circle around (2)} A two-dimensional image S(N) is composed of the partial images, which have been mutually put in position according to the positioning (step S19, S20).
{circle around (3)} Specific features of the obtained two-dimensional image S(N) are extracted for verification (step S22).
{circle around (4)} The extracted features are collated with specific features of a previously registered fingerprint (template) (step S23), and verification is completed when the features of the fingerprints match each other (step S24).
For the above-mentioned positioning ({circle around (1)}), Sequential Similarity Detection Algorithm (SSDA) is applicable. Let's say, for example, the first to (n−1)th (n: an integer 2 or more) frame images have been inputted and, as a result of the positioning and composition of the images, a partial composite image S(n−1; i, j) (i and j denote x-coordinate and y-coordinate, respectively) has been figured out. When the nth frame image f(n; i, j) is inputted thereto, it is positioned to the partial composite image S(n−1; i, j) to combine the images. In the positioning according to the SSDA method, the nth frame image f(n; i, j) is moved in parallel little by little and overlapped onto the- partial composite image S(n−1; i, j). Consequently, the best-matching position is determined as an optimal position of the frame image f(n; i, j). In order to implement the above operation, at the point where the frame image f(n; i, j) is translated by (x, y), cumulative error c(x, y) (referred to as penalty) in density levels of shading between two images is calculated by the following expression to find (x, y) with the minimum penalty c(x, y).
                              c          ⁡                      (                          x              ,              y                        )                          =                              ∑            i                    ⁢                                    ∑              j                        ⁢                                                                          S                  ⁡                                      (                                                                                            n                          -                          1                                                ;                        i                                            ,                      j                                        )                                                  -                                  f                  ⁡                                      (                                                                  n                        ;                                                  i                          -                          x                                                                    ,                                              j                        -                        y                                                              )                                                                                                                        (        1        )            Incidentally, two cumulative sums Σ are found over i and j regarding a certain area in the overlapping regions of the partial composite image S(n−1; i, j) and the frame image f(n; i, j).
In the above process {circle around (2)} for composing a two-dimensional image, the frame image f(n; i, j) is moved in parallel by (x, y) that achieve the minimum penalty c(x, y) and combined with the partial composite image S(n−1; i, j), and thus a new partial composite image S(n; i, j) is figured out.
However, according to the conventional technique, when the sweep (movement) rate of a finger against the sensor is high and the overlapping area between each frame is small, it is difficult to obtain the optimal distance of each inter-frame. That is, accurate positioning cannot be conducted when a user slides his/her finger swiftly, which causes a failure in reassembling a correct two-dimensional image, and thus the accuracy of fingerprint verification is deteriorated. To put it the other way around, a user is required to move his/her finger slowly in order to assure the stable collating operation, and thus causing degradation in usability.
As set forth hereinabove, in the conventional method and device for fingerprint verification, there is a problem that a user has to move his/her finger slowly on the sensor to improve the accuracy of fingerprint verification, and therefore usability of the device is deteriorated.
Problems that the Invention is to Solve
It is therefore an object of the present invention to provide a method and device for fingerprint identification enabling the precise positioning of inputted plural partial images by taking advantage of characteristics of information appliances for individuals that there are limited number of fingerprint data or templates of registered users, and thus realizing highly accurate fingerprint verification.
It is a further object of the present invention to reduce necessary calculations and speed up the process by achieving effective positioning, or to reduce the price of a computing unit used for the process as well as performing fingerprint verification with accuracy equal to, or higher than that of conventional verification with a sensor smaller than a conventional one, and thus realizing a low cost sensor and the wider range of applications.
It is a still further object of the present invention to provide a method and device for fingerprint identification; in which a moderately accurate verification result can be obtained at a higher speed, or with less computation when highly accurate verification is not required.